Improving the management of cardiovascular disease risk in primary care
Author: Mark R Nelson
Published online: 17 May 2021
We can learn from all clinical trials, whatever their outcomes
We can learn from all clinical trials, whatever their outcomes
Cardiovascular disease (CVD) prevention in Australian primary health care could be improved by effective strategies for better identifying and managing people who require medical care. Such strategies may include prompts to prescribe, the use of combination pills to simplify dosing regimens and reduce medication costs, and a systematic approach to ensuring lifelong adherence to prescribed therapies.
Webster and colleagues1 implemented a piloted, evidence‐based complex intervention in an appropriately designed cluster randomised trial that investigated the undertreatment of people at high risk of intermediate term adverse cardiovascular events, a recognised problem.2,3,4 The aims of the complex three‐component intervention were to identify such patients, initiate or intensify appropriate therapeutic prescribing, and ensure that prescribed medications were taken to facilitate the patients reaching individual risk factor goals (blood pressure, low‐density lipoprotein cholesterol levels). The intervention did not achieve its aims. Understanding why is important for designing and implementing future interventions.
One simple answer would be that compliance with the intervention was low for all three components. Webster and colleagues will publish the results of a mixed methods process evaluation of the trial in a separate article, but suggested that the complexity of the intervention, difficulties with integrating it into usual practice, uncertainty about the future availability of polypills, and inadequate reimbursement were possible factors. Until their process evaluation is published, this analysis remains speculative.
As with all novel work, barriers to success were likely at each of the health care system, patient, practice, and practitioner levels. Probable barriers included the intervention software being separate to the usual practice clinical software, the need to obtain individual written informed consent from patients for prescribing polypills, and the complexity of referral to the pharmacy‐based medication adherence support program and feedback on adherence to prescribers. The transient nature of a trial of an intervention that may or may not be applied more extensively in the future may have also made general practice staff reluctant to provide the considerable investment of time and effort required to implement it. Further, general practitioners and practice staff may not have fully understood the intervention itself, so that they fell back into familiar routines, maintaining current systems and modes of practice. It may also be that GPs did not consider the study to be of immediate interest to them or their patients, despite their voluntary participation.5
Therapeutic inertia, a perennial problem, is likely to have also been involved. Some responsibility in this regard may lie with the investigators; their focus on individual risk factors rather than absolute risk per se may have reinforced old individual risk factor management practices. The primary outcome was the proportion of patients with high CVD risk not receiving optimal preventive pharmacological therapy at baseline who achieved both blood pressure and low‐density lipoprotein cholesterol goals by study end. A more appropriate primary outcome would have been a measure of absolute risk, as indeed suggested by the title of the article. For example, smoking cessation, despite being the number one modifiable CVD risk factor, had no impact on the primary outcome, so that a doctor who prioritised this intervention over prescribing a statin would not influence the trial outcome, even had they achieved the largest reduction in CVD risk for their patient. Further, candidates for high absolute risk primary prevention who had blood pressure or low‐density lipoprotein cholesterol levels below traditional individual risk factor treatment thresholds and were therefore “undertreated” would remain so, as they were “already at goal”.
The investigators are to be congratulated on successfully conducting such a complex trial in general practice, but, to paraphrase Robert Burns, even the best laid plans of men often go awry.
Competing interests
No relevant disclosures.
References
- Webster R, Usherwood T, Joshi R, et al. An electronic decision support‐based complex intervention to improve management of cardiovascular risk in primary health care: a cluster randomised trial (INTEGRATE). Med J Aust 2021; 214: 420–427.
- Webster R, Patel A, Selak V, et al. SPACE Collaboration. Effectiveness of fixed dose combination medication (“polypills”) compared with usual care in patients with cardiovascular disease or at high risk: a prospective, individual patient data meta‐analysis of 3140 patients in six countries. Int J Cardiol 2016; 205: 147–156.
- Peiris D, Usherwood T, Panaretto K, et al. Effect of a computer‐guided, quality improvement program for cardiovascular disease risk management in primary health care: the treatment of cardiovascular risk using electronic decision support cluster‐randomized trial. Circ Cardiovasc Qual Outcomes 2015; 8: 87–95.
- Patel A, Cass A, Peiris D, et al. A pragmatic randomized trial of a polypill‐based strategy to improve use of indicated preventive treatments in people at high cardiovascular disease risk. Eur J Prev Cardiol 2015; 22: 920–930.
- Nelson MR. General practiced‐based clinical trials. Med J Aust 2013; 198: 136–137. https://www.mja.com.au/journal/2013/198/3/general-practice-based-clinical-trials
Linked content
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MJA Research: An electronic decision support‐based complex intervention to improve management of cardiovascular risk in primary health care: a cluster randomised trial (INTEGRATE)
Provenance: Commissioned; externally peer reviewed.